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Cross-spectral coherence and dynamic connectedness among contactless digital payments and digital communities, enterprise collaboration, and virtual reality firms

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  • Darehshiri, Mahsa
  • Ghaemi Asl, Mahdi
  • Babatunde Adekoya, Oluwasegun
  • Shahzad, Umer

Abstract

This paper examines the dynamic connectedness and risk transmissions among firms in the Future Payments and Future Communication businesses. In doing so, the authors employ the daily data of key variables of interest from May 15, 2017 to April 16, 2021. The study employs two empirical methodologies namely, the quantiles coherency and the time-varying parameter-vector autoregressive (TVP-VAR) model. While the former helps to determine the interdependence between Future Payments and the components of the Future Communication firms at different market states and investment horizons, the latter suitably addresses the time-varying connectedness among the series. The results from the quantiles coherence approach reveal a heterogeneous pattern of interdependency between Future Payments and each of the Future Communication firms, as it varies across different market states and investment horizons. The net connectedness findings further mention that Future Payments are net transmitters of shocks to other firms in the system, indicating that the firms play a leading role in the general contactless digital technology industry. These findings have theoretical, managerial, and policy implications, especially in terms of the improved adoption of these new technologies to the firms' financial infrastructures and the maintenance of an optimal investment portfolio.

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  • Darehshiri, Mahsa & Ghaemi Asl, Mahdi & Babatunde Adekoya, Oluwasegun & Shahzad, Umer, 2022. "Cross-spectral coherence and dynamic connectedness among contactless digital payments and digital communities, enterprise collaboration, and virtual reality firms," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    • Handle: RePEc:eee:tefoso:v:181:y:2022:i:c:s004016252200289x
    DOI: 10.1016/j.techfore.2022.121764
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